I probably should prove something beyond just my sense that it's happening, but I feel that the left side of the political spectrum, a little or a lot closer to where I belong than the other side, is becoming more like Republicans. We believe what we want to believe. Deficits suddenly don't matter any more. We don't like nuclear power and are suspicious of biomass so they're off the table instead of reasoned through. The Republicans careened into office with a president with zero political qualifications for any office, so the Democrats should nominate Oprah Winfrey. A weird and nuanced confrontation between (mostly) white teenagers, a weird cult, and a (not-Vietnam) Native American vet can only be thought of in a single way, and those who rethink it are the liberal version of cucks.
The big advantage America has over say, the UK, is that only one of our two major parties has gone bat-guano insane. We need to keep it that way and hopefully reduce that number over time. It's possible - here in California, Republicans are questionable as a major party (no statewide office in several election cycles, have only about 25% representation in the legislature), and maybe something reasonable will eventually overtake them.
I'm overplaying this a bit. The Oprah boomlet has mostly gone away, and the other issues get pushback. The left seems to be getting over the idea that race is a purely cultural construction but also has complex and nuanced relationship to genetics, one that doesn't fit simplistic racist constructions either.
It's a problem though, and reasonable people need to push back.
Saturday, January 26, 2019
Wednesday, January 23, 2019
Horn tooting
In today's San Jose Mercury News (moderately climate-related):
Opinion: Follow the will of voters and protect San Jose’s Coyote Valley
The 7,400-acre valley stretching from San Jose to Morgan Hill feeds our foothills and provides crucial drinking water
By BRIAN SCHMIDT
As the rains come and go through San Jose’s winter sky, the rainwater flows as both a blessing and a curse.
What we overlook is the natural function of the rain. One-third of our drinking water comes from local rains — not the distant Sierra — and offers a blessing for the working farmland that is an easy bike ride from San Jose’s southern edge. The water feeds the city’s green foothills and the animals in our habitat. It makes the streams navigated by our local fish and countless birds. The curse comes from human mismanagement that exacerbates floods, contaminates drinking water and changes the climate globally so we have either too much rain or too little.
Still, we control the curse, or at least the extent of it, and Tuesday San Jose’s leaders have the chance to act locally to protect land in Coyote Valley as a blessing for our community and the entire region.
This 7,400 acre valley, exactly south of South San Jose, is a gem of farmland and natural habitat that has so far stopped the Bay Area’s sprawl. In it lies the critical area where much of the rainwater as it is shed down from the hills – literally, the watershed – collects into Coyote Creek before being funneled into urban San Jose. In the confined stretches around urban streams, the San Jose floods of February 2017 had nowhere to go but into people’s homes. This tragedy could be compounded by mismanagement in the future, because Coyote Valley has long been slated for conversion from farmland and wetland to pavement, funneling still more flooding into San Jose.
The San Jose City Council on Tuesday afternoon will study Coyote Valley. San Jose’s voters set aside up to $50 million in the recently approved Measure T to buy and improve land for purposes of “water supply, flood control, open space and environmental protection of lands such as Coyote Valley.” Whether the council follows the will of 71 percent of the voters is at question, but clearly this valley is a natural sponge that shouldn’t be paved over.
Nor should councilmembers overlook the other reasons to protect Coyote Valley. The one-third of our drinking water from local rains ends up in our underground aquifer, including the valley. No other large area of that aquifer is so close and unprotected as Coyote Valley. The water ponded at the valley’s surface just this last weekend shows how the shallow depths to bedrock keep water near to the surface or even at the surface. We would never build a factory or an industrial warehouse in the middle of a drinking water reservoir, so why would we do that where the groundwater we drink touches the sky?
Still, this valley is under threat, from misguided ideas to replace undeveloped open land between San Jose and Morgan Hill with sprawl. The latest version of that threat would build vast warehouses, replacing Coyote Valley’s life with storage, all for a child’s handful of jobs and not the economic nirvana we were previously promised. This is not what San Jose needs or how the people voted.
The farmland and natural habitat come together here: bobcats, badgers, even mountain lions cross at the valley where mountain ranges come so close they almost kiss. San Jose’s ambitious climate plans mean developing up, not sprawling out.
The blessing that the rains bring, and the curse of our mishandling them, come together at Coyote Valley. San Jose can avoid that curse and create something beautiful by protecting Coyote Valley.
What we overlook is the natural function of the rain. One-third of our drinking water comes from local rains — not the distant Sierra — and offers a blessing for the working farmland that is an easy bike ride from San Jose’s southern edge. The water feeds the city’s green foothills and the animals in our habitat. It makes the streams navigated by our local fish and countless birds. The curse comes from human mismanagement that exacerbates floods, contaminates drinking water and changes the climate globally so we have either too much rain or too little.
Still, we control the curse, or at least the extent of it, and Tuesday San Jose’s leaders have the chance to act locally to protect land in Coyote Valley as a blessing for our community and the entire region.
This 7,400 acre valley, exactly south of South San Jose, is a gem of farmland and natural habitat that has so far stopped the Bay Area’s sprawl. In it lies the critical area where much of the rainwater as it is shed down from the hills – literally, the watershed – collects into Coyote Creek before being funneled into urban San Jose. In the confined stretches around urban streams, the San Jose floods of February 2017 had nowhere to go but into people’s homes. This tragedy could be compounded by mismanagement in the future, because Coyote Valley has long been slated for conversion from farmland and wetland to pavement, funneling still more flooding into San Jose.
The San Jose City Council on Tuesday afternoon will study Coyote Valley. San Jose’s voters set aside up to $50 million in the recently approved Measure T to buy and improve land for purposes of “water supply, flood control, open space and environmental protection of lands such as Coyote Valley.” Whether the council follows the will of 71 percent of the voters is at question, but clearly this valley is a natural sponge that shouldn’t be paved over.
Nor should councilmembers overlook the other reasons to protect Coyote Valley. The one-third of our drinking water from local rains ends up in our underground aquifer, including the valley. No other large area of that aquifer is so close and unprotected as Coyote Valley. The water ponded at the valley’s surface just this last weekend shows how the shallow depths to bedrock keep water near to the surface or even at the surface. We would never build a factory or an industrial warehouse in the middle of a drinking water reservoir, so why would we do that where the groundwater we drink touches the sky?
Still, this valley is under threat, from misguided ideas to replace undeveloped open land between San Jose and Morgan Hill with sprawl. The latest version of that threat would build vast warehouses, replacing Coyote Valley’s life with storage, all for a child’s handful of jobs and not the economic nirvana we were previously promised. This is not what San Jose needs or how the people voted.
The farmland and natural habitat come together here: bobcats, badgers, even mountain lions cross at the valley where mountain ranges come so close they almost kiss. San Jose’s ambitious climate plans mean developing up, not sprawling out.
The blessing that the rains bring, and the curse of our mishandling them, come together at Coyote Valley. San Jose can avoid that curse and create something beautiful by protecting Coyote Valley.
Brian Schmidt is the program director for the Greenbelt Alliance.
Tuesday, January 15, 2019
Gavin Explains It All
Well, Eli is retired so he is outsourcing to Gavin Schmidt who,explained it all in a series of tweets with the BlackPhysicists Tweeter. They actually, between them had a real conversation of value, which Eli here unrolls. Below the BlackPhysicists are in italic. Gavin does the rest. The sequence started with.
@BlackPhysicists Today our #iteachphysics topic is tools and pedagogy for teaching #weather and #climate physics. One goal of today's #iteachphysics chat is how do physics teachers include in the usual #physics curriculum, absent a specialized course, enough background and foundational knowledge to make our students better consumers of, explainers of #weather and #climate physics
I’d say to start with thermodynamics. Heat, density, convection and then Clausius-clapyeron. Condensation/evaporation and conservation of mass/energy, you have most of the principles. Coriolis rounds it off.
@BlackPhysicists In general #physics we do not spend a whole lot of time on classical #thermodynamics, but thermodynamics is essential in understanding #weather phenomena.
See hurricanes described as a Carnot cycle in @PhysicsToday
It doesn’t need to be all-in thermo, more just the concepts. PV=nRT, buoyancy, condensation...
@BlackPhysicists In almost every broadcast meteorologist's report we hear the term "weather model." What are weather models, exactly, and how do they work?
Here is another great animation of a weather model that includes atmospheric composition of aerosols (particulates):
And here is an excellent primer for climate models
@BlackPhysicists There are enough wildfires and volcano eruptions happening at one time to effect #weather on a large scale?
Good Q. Small volcanoes and fires add to the background climate for sure. Impacts on weather forecasts are more subtle, but by changing where solar/IR energy is absorbed/reflected they can affect temp gradients and hence dynamics.
@BlackPhysicists What do you think re: best practices to teach probability & stochasticity, parameterization & estimation, error and bias?
More Chaos theory/Lorentz attractor etc. Parameterisation and emergence are trickier but there are some @TEDTalks on that.
I generally don’t find that numerical analysis as taught is particularly useful though.
Dust can affect hurricane development (at least it has been hypothesized to). And smoke/aerosols impact air quality directly - something weather models are increasingly predicting as well.
@BlackPhysicists In fact the group at @NCASNews led by @vernon_morris is expert on dust from the Sahel leading to African Easterly Waves and Western Hemisphere hurricanes. I think in this presentation there a slide showing North American hurricane tracks emanating from the Senegal, Gambia area.
@BlackPhysicists Switching gears to #climate physics, in your experience do students have difficulty understanding the difference between weather and climate? This seems to be a major problem in TV punditry and probably most public discourse on weather and climate.
Actually no. Once explained - lots of good metaphors available - ppl generally get it. The ‘confusion’ one sees in punditry is fake - a position taken for rhetorical effect rather than any real misunderstanding.
Here’s a good metaphor. Climate is the clothes in your closet, weather is what you are wearing right now. The weather is constrained by the climate (you can’t wear clothes you don’t have), and the closet can change over time (new purchases/gifts), sometimes abruptly!
@BlackPhysicists What are the basic equations from #physics of a good climate model? What are the dichotomies (false or otherwise) between ‘weather’ models and ‘climate’ models?
Atmospheric physics is basically the same - slightly different levels of truncation (spatial resolution etc) since climate models have to run longer and with more components (oceans, sea ice, composition, biosphere (to some extent)). But major difference in conservation properties and ingestion of observations.
For a weather model, continual updating with observations means small businesses imbalances don’t matter much. But climate models don’t ingest obs like this so small biases can build (model ‘drift’). Conservation is key. Other issues are the diagnostics one is interested in. With weather, you want the specific trajectory of storms/fronts etc, with climate you want the statistical description (how many storms/what tracks) because that is where the skill is.
Actually, understanding the notion of skill is key for both kinds of model - how can you judge if a model is useful despite it not being perfect?
@BlackPhysicists @RogerAPielkeSr offers a lot of great resources in both #weather and #climate. One defn he's offered: Definition 1:Weather is separated by climate just by averaging time period; e.g. a 30 year time average temperature we call "climate"
That’s been true historically, but that’s a little arbitrary and not fundamental. I would prefer a distinction based on forecasts of specific trajectories vs statistics of trajectories. An example might help.
@BlackPhysicists Right, it is possible, even necessary, to draw a distinction between a time average and more detailed statistics, even as basic as the meaning of standard deviation. That is an important point I think that's lost in a lot intro measurement in #physics
Take Mt Pinatubo eruption. A very large forcing on the climate system, which had detectable impacts on rainfall, temperature, wind patterns. It didn’t extend the predictability of weather forecasts, however the statistical impacts were predicted skillfully by climate models.
Those climate forecasts were for 1, 2, 3 years out. Much shorter than the ‘30 year’ period you mentioned. The issue is one of signal and noise. For slow changes in forcings (or none), 30 years is a good period to average out a lot of internal variability. But for a big signal (like Pinatubo), the climate impacts easily exceed the ‘noise’ of the weather. Same with the seasons! (Note ‘noise’ here isn’t pejorative- one person’s noise is another’s signal after all). Bottom line, there is no longer single time period that separates weather and climate.
@BlackPhysicists I think a key bridge to build in the #physics curriculum is micro- meso- scale physics of how these things, aerosols, dust, etc affect #weather and #climate. That and the spectral decomposition of light and its effects
How do you bridge weather models' that are built on 1st principle physics (continuity, Navier-Stokes, advection-diffusion of energy) to climate models? The latter isn't just long-time simulations of the former on meaningful grids and timesteps?
This is of course intended to be a counter-positional question 🤓 #
They aren’t different in principle. But all these models need to have a scale (in time/space) below which they are not resolving the ‘true’ equations. For weather models that scale is a little smaller than for climate models, but for both it’s getting smaller over time.
@BlackPhysicists And that is an important point that I think a lot of people don't get about computational physics, i.e., that pushing computational limits possibly/likely will reveal new physics just like increasing resolution, repetition rate etc of measurement does
@BlackPhysicists Jan 12 More #iteachphysics @ClimateOfGavin you've been a great help today. Before we end, there are 2 related concepts sea surface temperature and ocean heat content. How can we best explain to students the difference between the two?
More Sea surface temperature is a diagnostic of what’s happening at the surface (duh!). It’s the field that has the direct connection to the atmosphere (via radiation, evap etc.). It is changes in SST that allow for the planet to requilibirate to any change in radiative forcing.
But ocean heat content changes writ large are tied to the planetary imbalance (how much more energy are we bringing in than losing to space). It was predicted in the 1980s that if the predictions of global warming were right for the right reasons, the signal would be in the OHC
Some discussions of that here in the light of recent updates and discussions:
@BlackPhysicists If you have time, could you give your take home message from the @NatureClimate paper that was in the news this week.
@BlackPhysicists I think I meant this report, which is more from an IPCC report at not the @NatureClimate paper.
It's kind of covered in the @RealClimate piece I tweeted earlier. As non-climatic artifacts are removed from the OHC analyses and more data is being ingested from Argo etc, the predictions from GCMs are being nicely validated.
@BlackPhysicists Today our #iteachphysics topic is tools and pedagogy for teaching #weather and #climate physics. One goal of today's #iteachphysics chat is how do physics teachers include in the usual #physics curriculum, absent a specialized course, enough background and foundational knowledge to make our students better consumers of, explainers of #weather and #climate physics
I’d say to start with thermodynamics. Heat, density, convection and then Clausius-clapyeron. Condensation/evaporation and conservation of mass/energy, you have most of the principles. Coriolis rounds it off.
@BlackPhysicists In general #physics we do not spend a whole lot of time on classical #thermodynamics, but thermodynamics is essential in understanding #weather phenomena.
See hurricanes described as a Carnot cycle in @PhysicsToday 
@BlackPhysicists In almost every broadcast meteorologist's report we hear the term "weather model." What are weather models, exactly, and how do they work?
Here is another great animation of a weather model that includes atmospheric composition of aerosols (particulates):
@BlackPhysicists There are enough wildfires and volcano eruptions happening at one time to effect #weather on a large scale?
Good Q. Small volcanoes and fires add to the background climate for sure. Impacts on weather forecasts are more subtle, but by changing where solar/IR energy is absorbed/reflected they can affect temp gradients and hence dynamics.
@BlackPhysicists What do you think re: best practices to teach probability & stochasticity, parameterization & estimation, error and bias?
More Chaos theory/Lorentz attractor etc. Parameterisation and emergence are trickier but there are some @TEDTalks on that.
I generally don’t find that numerical analysis as taught is particularly useful though.
Dust can affect hurricane development (at least it has been hypothesized to). And smoke/aerosols impact air quality directly - something weather models are increasingly predicting as well.
@BlackPhysicists In fact the group at @NCASNews led by @vernon_morris is expert on dust from the Sahel leading to African Easterly Waves and Western Hemisphere hurricanes. I think in this presentation there a slide showing North American hurricane tracks emanating from the Senegal, Gambia area.
@BlackPhysicists Switching gears to #climate physics, in your experience do students have difficulty understanding the difference between weather and climate? This seems to be a major problem in TV punditry and probably most public discourse on weather and climate.
Actually no. Once explained - lots of good metaphors available - ppl generally get it. The ‘confusion’ one sees in punditry is fake - a position taken for rhetorical effect rather than any real misunderstanding.
Here’s a good metaphor. Climate is the clothes in your closet, weather is what you are wearing right now. The weather is constrained by the climate (you can’t wear clothes you don’t have), and the closet can change over time (new purchases/gifts), sometimes abruptly!
@BlackPhysicists What are the basic equations from #physics of a good climate model? What are the dichotomies (false or otherwise) between ‘weather’ models and ‘climate’ models?
Atmospheric physics is basically the same - slightly different levels of truncation (spatial resolution etc) since climate models have to run longer and with more components (oceans, sea ice, composition, biosphere (to some extent)). But major difference in conservation properties and ingestion of observations.
For a weather model, continual updating with observations means small businesses imbalances don’t matter much. But climate models don’t ingest obs like this so small biases can build (model ‘drift’). Conservation is key. Other issues are the diagnostics one is interested in. With weather, you want the specific trajectory of storms/fronts etc, with climate you want the statistical description (how many storms/what tracks) because that is where the skill is.
Actually, understanding the notion of skill is key for both kinds of model - how can you judge if a model is useful despite it not being perfect?
@BlackPhysicists @RogerAPielkeSr offers a lot of great resources in both #weather and #climate. One defn he's offered: Definition 1:Weather is separated by climate just by averaging time period; e.g. a 30 year time average temperature we call "climate"
That’s been true historically, but that’s a little arbitrary and not fundamental. I would prefer a distinction based on forecasts of specific trajectories vs statistics of trajectories. An example might help.
@BlackPhysicists Right, it is possible, even necessary, to draw a distinction between a time average and more detailed statistics, even as basic as the meaning of standard deviation. That is an important point I think that's lost in a lot intro measurement in #physics
Take Mt Pinatubo eruption. A very large forcing on the climate system, which had detectable impacts on rainfall, temperature, wind patterns. It didn’t extend the predictability of weather forecasts, however the statistical impacts were predicted skillfully by climate models.
Those climate forecasts were for 1, 2, 3 years out. Much shorter than the ‘30 year’ period you mentioned. The issue is one of signal and noise. For slow changes in forcings (or none), 30 years is a good period to average out a lot of internal variability. But for a big signal (like Pinatubo), the climate impacts easily exceed the ‘noise’ of the weather. Same with the seasons! (Note ‘noise’ here isn’t pejorative- one person’s noise is another’s signal after all). Bottom line, there is no longer single time period that separates weather and climate.
@BlackPhysicists I think a key bridge to build in the #physics curriculum is micro- meso- scale physics of how these things, aerosols, dust, etc affect #weather and #climate. That and the spectral decomposition of light and its effects
How do you bridge weather models' that are built on 1st principle physics (continuity, Navier-Stokes, advection-diffusion of energy) to climate models? The latter isn't just long-time simulations of the former on meaningful grids and timesteps?
This is of course intended to be a counter-positional question 🤓 #
They aren’t different in principle. But all these models need to have a scale (in time/space) below which they are not resolving the ‘true’ equations. For weather models that scale is a little smaller than for climate models, but for both it’s getting smaller over time.
@BlackPhysicists And that is an important point that I think a lot of people don't get about computational physics, i.e., that pushing computational limits possibly/likely will reveal new physics just like increasing resolution, repetition rate etc of measurement does
@BlackPhysicists Jan 12 More #iteachphysics @ClimateOfGavin you've been a great help today. Before we end, there are 2 related concepts sea surface temperature and ocean heat content. How can we best explain to students the difference between the two?
More Sea surface temperature is a diagnostic of what’s happening at the surface (duh!). It’s the field that has the direct connection to the atmosphere (via radiation, evap etc.). It is changes in SST that allow for the planet to requilibirate to any change in radiative forcing.
But ocean heat content changes writ large are tied to the planetary imbalance (how much more energy are we bringing in than losing to space). It was predicted in the 1980s that if the predictions of global warming were right for the right reasons, the signal would be in the OHC
Some discussions of that here in the light of recent updates and discussions:
@BlackPhysicists If you have time, could you give your take home message from the @NatureClimate paper that was in the news this week.
@BlackPhysicists I think I meant this report, which is more from an IPCC report at not the @NatureClimate paper.
It's kind of covered in the @RealClimate piece I tweeted earlier. As non-climatic artifacts are removed from the OHC analyses and more data is being ingested from Argo etc, the predictions from GCMs are being nicely validated.